sustainability
Article Numerical Simulation and Design of Multi-Tower Concentrated Solar Power Fields
Zaharaddeen Ali Hussaini 1,2,*, Peter King 1 and Chris Sansom 1 1 School of Water Energy and Environment, Cranfield University, Cranfield MK43 0AL, UK; peter.king@cranfield.ac.uk (P.K.); c.l.sansom@cranfield.ac.uk (C.S.) 2 Centre for Renewable Energy Research, Bayero University, Kano 700241, Nigeria * Correspondence: zaharaddeen-ali.hussaini@cranfield.ac.uk or [email protected]
Received: 7 February 2020; Accepted: 10 March 2020; Published: 19 March 2020
Abstract: In power tower systems, the heliostat field is one of the essential subsystems in the plant due to its significant contribution to the plant’s overall power losses and total plant investment cost. The design and optimization of the heliostat field is hence an active area of research, with new field improvement processes and configurations being actively investigated. In this paper, a different configuration of a multi-tower field is explored. This involves adding an auxiliary tower to the field of a conventional power tower Concentrated Solar Power (CSP) system. The choice of the position of the auxiliary tower was based on the region in the field which has the least effective reflecting heliostats. The multi-tower configuration was initially applied to a 50 MWth conventional field in the case study region of Nigeria. The results from an optimized field show a marked increase in the annual thermal energy output and mean annual efficiency of the field. The biggest improvement in the optical efficiency loss factors be seen from the cosine, which records an improvement of 6.63%. Due to the size of the field, a minimal increment of 3020 MWht in the Levelized Cost of Heat (LCOH) was, however, recorded. In much larger fields, though, a higher number of weaker heliostats were witnessed in the field. The auxiliary tower in the field provides an alternate aim point for the weaker heliostat, thereby considerably cutting down on some optical losses, which in turn gives rise to higher energy output. At 400 MWth, the multi-tower field configuration provides a lower LCOH than the single conventional power tower field.
Keywords: concentrated solar power; field layout; heliostat field; multi-tower field
1. Introduction Due to the declining patronage of nuclear energy and volatile petroleum and natural gas prices, coupled with the rising global temperature, predominately due to the atmospheric build-up of CO2, nations at large are opting for and considering renewable energy technologies for their power generation. Solar energy, in particular, is seen as an extremely viable option, especially in areas with good solar insolation [1]. Solar thermal energy for electricity generation is typically referred to as Concentrated Solar Power (CSP) [2]. CSP can be a driving force in the cause of reducing CO2 emission, thereby contributing to reducing and limiting the global temperature increase. Of the existing types of CSP, power tower systems are one of the most promising solar thermal technologies. This is mainly due to their ability to offer higher temperatures and, hence, higher efficiencies [2–7]. In power tower systems, the heliostat field is one of the essential subsystems. This is due to its significant contribution to the plant’s total investment cost: about 40%–50% of the plant’s cost is attributed to the heliostat field [8–12]. The field contributes equally to the plant’s overall power losses of about 40% [8,13–16]. It has hence become essential to ensure that the field layout is optimal at collecting energy from the sun. The design and optimization of the heliostat field is hence an
Sustainability 2020, 12, 2402; doi:10.3390/su12062402 www.mdpi.com/journal/sustainability Sustainability 2020, 12, 2402 2 of 22 active area of research, with new field improvement processes being actively investigated. Several methods have been proposed in the literature to improve heliostat field efficiencies and reduce losses, either by improving through optimization or by suggesting new heliostat field layout patterns and configurations entirely. Several literatures that focus on heliostat field layout patterns and configurations are available. In Noone et al.’s [8] work, for example, a spiral field pattern inspired by disc phyllotaxis is introduced, which is applied in heliostat field design and optimization. By redesigning the layout of the PS10 field using the algorithm, an improvement in the optical efficiency and a reduction in the land area utilized is witnessed. E. Carrizosa et al. [17] presented a pattern-free heliostat field layout distribution style, obtained by the simultaneous optimization of both the heliostat field (heliostat locations and number) and the tower (tower height and receiver size). Cadiz et al. [10] presented shadowing and blocking optimization procedures for a variable-geometry heliostat field. The variable-geometry concept explored by the author allows the possibility of minimizing the cosine losses by rotating the entire field. In a similar vein, Mohammed Aldulaimi and MS Soylemez [14] suggested a new heliostat field layout arrangement by identifying heliostats with low optical efficiency and increasing their heights in a bid to curb blocking losses and hence increase the total annual field efficiency. Emilo Carrizosa [18] also suggested some alterations in the field by considering a field with different heliostat sizes. Mani Yousefpour Lazardjan [19] presented a tool developed at Solar-Insitut Julich (SIJ) primarily for the optimization of a novel micro-heliostat concept. In a novel and unconventional heliostat field layout design, Danielli et al. [20] developed the concatenated micro-tower (CMT). In this configuration, dynamic receivers mounted on arrays of small towers enable heliostats in mini subfields to direct sunlight with minimal cosine losses, thus improving the field’s overall optical efficiency. N. Cruz et al. [21] also developed an algorithm using a genetic algorithm that generates a continuous pattern-free field layout. The algorithm developed, using parallelization, provides a solution to the conceptual complexity and high computational cost associated with pattern-free heliostat field optimization. Arrif et al. [22] also developed an algorithm which is based on the bee colony optimization method to optimize the case study site of the PS10 CSP power plant in Spain. The proposed algorithm, the Artificial Bee Colony Algorithm (IABCA), finds the best position for each heliostat on the field in which the maximum efficiency for both the heliostat and field is reached within a limited area. L Deng et al. [23] proposed a new pattern for the heliostat field layout: a rose pattern based on the classic radial staggered configuration. The pattern divides the radial staggered configuration into six sectors, and some of those sectors are then optimized separately using advanced differential equation algorithm, thus increasing the optimization variables. In another unconventional heliostat field layout design, additional towers, each having its receiver mounted atop, are introduced in the field. Although it is only recently that the multi-tower setup has attracted much interest in the research community, the configuration has been explored in the past. In 1999, Romero et al. [24] pointed out that centralized large solar power tower plants are at odds with the increasing shift towards a distributed-energy setup and could hence face future deployment difficulties. They proposed and analyzed how small tower fields could be integrated into a Modular Integrated Utility Systems (MIUS) approach, in order to fully exploit the advantages of a distributed-energy setup in a community. In 2002, Schramek and Mills [25] proposed a Multi-Tower Solar Array (MTSA) system, which consists of a collection of solar towers densely grouped together, thereby allowing for partial overlapping of the heliostats in the field, and hence allowing greater utilization of the solar radiation falling on the unused ground area in the field. In a more recent work, in 2012, Augsburger and Favrat [26] proposed a method in which each individual heliostat is instantaneously aimed at a receiver in a multi-tower setup, following an aim selection criterion. The thermo-economic performance of a three-tower heliostat field was then evaluated using a model. In another work, eSolar and Inc. (B&W PGG) [27] investigated the use of small heliostats with multiple receivers and towers [27]. They proposed a configuration with 14 molten salt power towers, for a 100 MWe (net) power block that is capable of delivering a Sustainability 2020, 12, 2402 3 of 22
75%Sustainability capacity factor.2017, 9, x Tyner FOR PEER and REVIEW Wasyluk [28] presented a follow-through on the conceptual design3 of 22 previously developed by eSolar and Inc., where several trade studies were carried out in order to arrive carried out in order to arrive at the optimally cost-effective system configuration for the multi-tower at the optimally cost-effective system configuration for the multi-tower setup. The concept proposed setup. The concept proposed involves replicating the field, without scaling or redesign, in order to involves replicating the field, without scaling or redesign, in order to meet the capacity required. meet the capacity required. In another work by Pasha Piroozmand and Mehrdad [29], an iterative In another work by Pasha Piroozmand and Mehrdad [29], an iterative algorithm was developed in algorithm was developed in order to obtain the optimum instantaneous efficiency of the heliostat in order to obtain the optimum instantaneous efficiency of the heliostat in the field when selecting the the field when selecting the tower which radiation will be reflected onto in a two-tower field set up, tower which radiation will be reflected onto in a two-tower field set up, so as to maximize the annual so as to maximize the annual optical efficiency of the field. As a case study, the authors used Particle optical efficiency of the field. As a case study, the authors used Particle Swarm Optimization (PSO) to Swarm Optimization (PSO) to optimally design a two-tower spiral patterned field along the east-west optimally design a two-tower spiral patterned field along the east-west line before redesigning the line before redesigning the field using the iterative method. The authors here noted that issues such field using the iterative method. The authors here noted that issues such as field layouts and aiming as field layouts and aiming strategies need to be further investigated in order to achieve a more strategies need to be further investigated in order to achieve a more optimized and comprehensive optimized and comprehensive multi-tower system. In 2018, Vast Solar, an Australian company multi-tower system. In 2018, Vast Solar, an Australian company engaged in CSP research, developed engaged in CSP research, developed and commissioned a 1.1MWe pilot plant utilizing a modular and commissioned a 1.1MWe pilot plant utilizing a modular solar array field [30]. Each of the five solar array field [30]. Each of the five modular arrays in the field has a dedicated tower in which the modular arrays in the field has a dedicated tower in which the Heat Transfer Fluid (HTF) is heated Heat Transfer Fluid (HTF) is heated at the receiver. The multiple towers are connected to a central at the receiver. The multiple towers are connected to a central thermal storage unit. The company is thermal storage unit. The company is already planning to go further by developing a 30MW already planning to go further by developing a 30MW commercial demonstration project in Australia commercial demonstration project in Australia using the modular array field. using the modular array field. In all the multi-tower configurations reviewed, each tower has its own heliostat field, which In all the multi-tower configurations reviewed, each tower has its own heliostat field, which replaces an entire field with surrounding heliostats in smaller units until the capacity required is met. replaces an entire field with surrounding heliostats in smaller units until the capacity required is met. In this paper, a different architecture of the multi-tower configuration is investigated. The In this paper, a different architecture of the multi-tower configuration is investigated. The configuration configuration explored, which provides an alternate viewpoint to the usual mainstream multi-tower explored, which provides an alternate viewpoint to the usual mainstream multi-tower configuration, configuration, involves adding an auxiliary tower to an existing surrounding field. The paper initially involves adding an auxiliary tower to an existing surrounding field. The paper initially begins by begins by defining the models used for the development of a conventional heliostat field. After model defining the models used for the development of a conventional heliostat field. After model validation, validation, a 50MWth solar field was simulated in Nigeria, with the objective function being the a 50 MWth solar field was simulated in Nigeria, with the objective function being the Levelized Cost of Levelized Cost of Heat (LCOH). An auxiliary tower was then added onto the existing field, and its Heat (LCOH). An auxiliary tower was then added onto the existing field, and its effects investigated. effects investigated. The results from the optimized multi-tower configuration were then compared The results from the optimized multi-tower configuration were then compared with conventional with conventional fields at different thermal field powers, in order to determine the optimum fields at different thermal field powers, in order to determine the optimum transition size from a single transition size from a single field to a multi-tower field. field to a multi-tower field.
2. Model2. Model Description Description
2.1.2.1. Solar Solar Insolation, Insolation, Time Time and and Angles Angles FindingFinding the the position position of the of the sun sun is one is one of the of the very very first first steps steps that that needs needs to be to taken.be taken. The The position position cancan be characterizedbe characterized by the by altitudethe altitude (α) and (α) azimuthand azimuth angle angle (γs). Figure (γs). Figure1 shows 1 shows the angles the definingangles defining the apparentthe apparent position position of the sun of the [12 ,sun31]. [12,31],
Figure 1. Position of the sun relative to the collector. Figure 1. Position of the sun relative to the collector.
where is the zenith angle and Sx, Sy, and Sz denote the vector components of the sun’s radiation. The solar altitude is given by Equation 1 [31]: Sustainability 2020, 12, 2402 4 of 22
→ Where θz is the zenith angle and Sx, Sy, and Sz denote the vector components S of the sun’s radiation. The solar altitude is given by Equation (1) [31]:
Sinα = SinϕSinδ + CosϕCosδCosω (1) where latitude, ϕ, is angular location relative to the equator, and declination angle, δ, is the angular position of the sun at solar noon on the equatorial plane. The declination angle is given by Equation (2):
284 + n δ = 23.45Sin 360 (2) × 365 where n represents the day number of the year [31], and ω is the Hour angle (east or west angular displacement of the sun about the local meridian due to earth’s rotation about its polar axis). It is represented in Equation (3), with t being the solar time [31].
ω = 15 (t 12) (3) × − The azimuth angle, on the other hand, is given by Equation (4) [31]
CosδSinω Sinγ = (4) s Cosα Specific geographical locations in Nigeria are highly suitable for the deployment of solar energy technologies, especially in the northern parts of the country. For regions in the northern parts of Nigeria, a Direct Normal Irradiance (DNI) average value of around 5.5 kWh/m2/day is obtainable [32–34], making the area suitable for CSP deployment. The solar insolation at the selected site, Katsina, Nigeria (Latitude: 12.39◦ N Longitude: 7.60◦ E), was obtained from the metrological agency in Nigeria, NiMet (Nigerian Metrological Agency). The DNI at the identified site averages out to 5.53 kWh/m2/day.
2.2. Optical Efficiency The optical efficiency of the field measures the capability of each heliostat to concentrate and reflect radiation to the receiver. Every heliostat has a particular optical efficiency value due to its position in the field and its interaction with the other elements in the field. The overall value for the field is then calculated by averaging each particular result. The optical field efficiency is expressed by Equation (5) [8,12,35]; η = η η η η η (5) f ield cos × sb × att × int × re f where ηcos, ηsb, ηatt, ηint, and ηre f represent losses due to cosine, shadowing and blocking, atmospheric attenuation, interception and mirror reflectivity factors, respectively. Maximizing field efficiency is an important task that ensures the optical losses are reduced as much as possible.
2.2.1. Cosine Efficiency Loss The cosine efficiency loss is one of the most critical energy loss sources in heliostat fields and often represents the most significant loss term [36]. It is defined as the cosine of the angle formed by the incident solar beam radiation and the vector normal to the reflective heliostat surface [37]. The efficiency factor depends on both the position of the sun and of the heliostat [12]. Figure2 shows the effect of cosine on reflected rays from the heliostat. To evaluate the normal vector of the heliostat surface, two other vectors need to be defined, i.e., the vectors from the center of the heliostat to the sun, →S, and those to the desired image location on Sustainability 2020, 12, 2402 5 of 22
the receiver surface, →r . Assuming x, y, and z are the coordinates of the heliostat center, and TH is the tower height, the components of the unit vector of the reflected ray, →r is given by Equation (6) [38,39]: x y (TH z) → r = q − , q − , q − (6) 2 2 2 x2 + y2 + (TH z) x2 + y2 + (TH z) x2 + y2 + (TH z) Sustainability 2017, 9, x FOR PEER REVIEW − − − 5 of 22
Figure 2. Figure showing the effect of cosine on reflected rays in Heliostat A and B. Figure 2. Figure showing the effect of cosine on reflected rays in Heliostat A and B. Vector →S components are formed from Figure1. With →S and →r defined, the components of the unit vector normal of the heliostat surface can then be evaluated (Equation (7)): To evaluate the normal vector of the heliostat surface, two other vectors need to be defined, i.e., the vectors from the center of the heliostat to the →sun,S + →r , and those to the desired image location on m→ = (7) the receiver surface, . Assuming x, y, and z are the →S + coordinate→r s of the heliostat center, and TH is the tower height, the components of the unit vector of the reflected ray, is given by Equation 6 [38,39]:
The cosine efficiency− can now be calculated as the− dot product of the unitary( vectors − ) m→ and →S, as shown in = Equation (8): , , (6) + +( − ) + +( − ) + +( − ) η = m→ →S (8) cos · Vector components are formed from Figure 1. With and defined, the components of the 2.2.2. Shadowing and Blocking Efficiency Loss unit vector normal of the heliostat surface can then be evaluated (Equation 7): Shadowing and blocking losses are a result of the reduction of the heliostat’s useful area due to the presence of a heliostat in the path of the incident radiation+ or to reflected radiation, respectively. = (7) In Figure3, the contour of the representative heliostat + and the projected contour of the two adjacent heliostats in a radial staggered configuration is shown. The cosineHere, efficiency bh and bw can are the now blocking be calculated and shadowing as the portions dot product of the representative of the unitary heliostat. vectors LH and and , as shownLW in are Equation the heliostat’s 8: length and width, respectively. DM is the diameter of the heliostat, inclusive of dsep (the extra security distance between adjacent heliostats).
The blocking and shadowing model adopted = the ⋅ simplified calculation method developed by (8) Sassi [40], using the outline projections of the neighboring heliostats. This method divides the surfaces of each heliostat into strips, and those strips identified to have potential for shadowing and blocking 2.2.2. Shadowingare projected and onto Blocking the surface Efficiency of the problem Loss heliostat. Among all the shading and blocking projections, the maximum height is selected for each strip. The fraction of the area free from shading and blocking Shadowinggives the shadingand blocking and blocking losses effi areciency a result value. of the reduction of the heliostat’s useful area due to the presenceAs of toa heliostat the identification in the path and selection of the incide of thent shadowing radiation and or blockingto reflected heliostats, radiation, the method respectively. In Figureoutlined 3, the contour in [37] by of Besarati the representative and Goswami is helio adopted.stat Thisand methodology the projected considers contour only of a the subset two of adjacent heliostatsthe in heliostats a radial that staggered have a high configuration potential for shadowingis shown. and blocking. For shading, a circle of radius
Figure 3. Blocking showing the contour of the representative heliostat and the projected contour of two adjacent heliostats in the first-row. Sustainability 2017, 9, x FOR PEER REVIEW 5 of 22
Figure 2. Figure showing the effect of cosine on reflected rays in Heliostat A and B.
To evaluate the normal vector of the heliostat surface, two other vectors need to be defined, i.e., the vectors from the center of the heliostat to the sun, , and those to the desired image location on the receiver surface, . Assuming x, y, and z are the coordinates of the heliostat center, and TH is the tower height, the components of the unit vector of the reflected ray, is given by Equation 6 [38,39]: − − ( − ) = , , (6) + +( − ) + +( − ) + +( − )
Vector components are formed from Figure 1. With and defined, the components of the unit vector normal of the heliostat surface can then be evaluated (Equation 7): + = (7) +
The cosine efficiency can now be calculated as the dot product of the unitary vectors and , as shown in Equation 8: